We evaluate FedCG's performance by first comparing its averaged clients' accuracy with those of 6 baselines in 6 scenarios. Table REF  reports the results. It shows that FedCG achieves the best accuracy in 4 out of 6 scenarios, demonstrating its competitive performance. More specifically, FedCG achieves the best accuracy in all 3 non-IID scenarios. In particular, it outperforms the-next-best-performing FedProx by 4.35% on Office. In IID scenarios, FedAvg, FedProx and FedDF have an edge in that they aggregate full local networks trained directly from original local data while there is no negative transfer effect caused by data heterogeneity [1]}. As a result, they perform better than FedCG overall, on CIFAR10 particularly. However, they are vulnerable to DLG attacks, as we will discuss in the next section.
